“…The results in this paper extend those of [12] in two significative aspects. On the one hand, the state space of the chains need not be the same, which is a basic assumption in the construction of order-preserving couplings as considered in [12].…”
Section: Introductionsupporting
confidence: 86%
“…The results in this paper extend those of [12] in two significative aspects. On the one hand, the state space of the chains need not be the same, which is a basic assumption in the construction of order-preserving couplings as considered in [12]. On the other hand, when the state spaces coincide, the set K where the coupling is required to stay is completely arbitrary (in particular, it need not be induced by a pre-ordering on E).…”
Section: Introductionsupporting
confidence: 86%
“…This is the object of Theorem 2, which shows that the points of E having some properties related with the structure of K need not be duplicated for the construction of the coupling. In fact, when K is defined by a pre-ordering on E, the construction of the coupling given in Theorem 2 coincides with the case of order-preserving couplings on partially ordered spaces [12].…”
Section: Introductionmentioning
confidence: 84%
“…Kamae et al [6] study the relationship between stochastic comparison on partially ordered Polish spaces and couplings, showing that (X t ) is stochastically dominated by (Y t ) if and only if there exists an order-preserving coupling of (X t ) and (Y t ), that is, a coupling (Z t ) such that P z (Z t ∈ K) = 1 for all t > 0 if z ∈ K, where K = {z = (x, y) : x ≤ y} and P z (Z t ∈ K) denotes the probability of the event {Z t ∈ K} when starting from z. In [12] it is shown that if (X t ) and (Y t ) are continuous-time Markov chains on a partially ordered countable set E and (X t ) is stochastically dominated by (Y t ), then the order-preserving coupling (Z t ) can be chosen to be a Markov chain (i.e. a Markovian coupling); also, a way to construct the coupling is given.…”
Section: Introductionmentioning
confidence: 99%
“…In this paper, we completely solve the aforementioned problem for general Markov chains (Theorem 1) without any hypotheses on the rates or the structure of K. Our approach relies on the definition of a pre-ordering on E ∪ F based on K and the use of the ideas and results in [12]. This will allow us to get necessary and sufficient conditions on the rates for the existence of a K-coupling.…”
Let (Xt) and (Yt) be continuous-time Markov chains with countable state spaces E and F and let K be an arbitrary subset of E x F. We give necessary and sufficient conditions on the transition rates of (Xt) and (Yt) for the existence of a coupling which stays in K. We also show that when such a coupling exists, it can be chosen to be Markovian and give a way to construct it. In the case E=F and K ⊆ E x E, we see how the problem of construction of the coupling can be simplified. We give some examples of use and application of our results, including a new concept of lumpability in Markov chains.
“…The results in this paper extend those of [12] in two significative aspects. On the one hand, the state space of the chains need not be the same, which is a basic assumption in the construction of order-preserving couplings as considered in [12].…”
Section: Introductionsupporting
confidence: 86%
“…The results in this paper extend those of [12] in two significative aspects. On the one hand, the state space of the chains need not be the same, which is a basic assumption in the construction of order-preserving couplings as considered in [12]. On the other hand, when the state spaces coincide, the set K where the coupling is required to stay is completely arbitrary (in particular, it need not be induced by a pre-ordering on E).…”
Section: Introductionsupporting
confidence: 86%
“…This is the object of Theorem 2, which shows that the points of E having some properties related with the structure of K need not be duplicated for the construction of the coupling. In fact, when K is defined by a pre-ordering on E, the construction of the coupling given in Theorem 2 coincides with the case of order-preserving couplings on partially ordered spaces [12].…”
Section: Introductionmentioning
confidence: 84%
“…Kamae et al [6] study the relationship between stochastic comparison on partially ordered Polish spaces and couplings, showing that (X t ) is stochastically dominated by (Y t ) if and only if there exists an order-preserving coupling of (X t ) and (Y t ), that is, a coupling (Z t ) such that P z (Z t ∈ K) = 1 for all t > 0 if z ∈ K, where K = {z = (x, y) : x ≤ y} and P z (Z t ∈ K) denotes the probability of the event {Z t ∈ K} when starting from z. In [12] it is shown that if (X t ) and (Y t ) are continuous-time Markov chains on a partially ordered countable set E and (X t ) is stochastically dominated by (Y t ), then the order-preserving coupling (Z t ) can be chosen to be a Markov chain (i.e. a Markovian coupling); also, a way to construct the coupling is given.…”
Section: Introductionmentioning
confidence: 99%
“…In this paper, we completely solve the aforementioned problem for general Markov chains (Theorem 1) without any hypotheses on the rates or the structure of K. Our approach relies on the definition of a pre-ordering on E ∪ F based on K and the use of the ideas and results in [12]. This will allow us to get necessary and sufficient conditions on the rates for the existence of a K-coupling.…”
Let (Xt) and (Yt) be continuous-time Markov chains with countable state spaces E and F and let K be an arbitrary subset of E x F. We give necessary and sufficient conditions on the transition rates of (Xt) and (Yt) for the existence of a coupling which stays in K. We also show that when such a coupling exists, it can be chosen to be Markovian and give a way to construct it. In the case E=F and K ⊆ E x E, we see how the problem of construction of the coupling can be simplified. We give some examples of use and application of our results, including a new concept of lumpability in Markov chains.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.